Backwards Approximate Dynamic Programming for Wind Power Plants with Hybrid Energy Storage Systems
International Journal of Production Economics (IJPE) 238 (2021), 108155, doi: 10.1016/j.ijpe.2021.108155
31 Pages Posted: 10 May 2021 Last revised: 14 Apr 2022
Date Written: May 3, 2021
Abstract
On most modern energy markets, electricity is traded in advance and a power producer has to commit to deliver a certain amount of electricity some time before the actual delivery. This is especially difficult for power producers with renewable energy sources that are stochastic (like wind and solar). Thus, short-term electricity storages like batteries are used to increase flexibility. By contrast, long-term storages allow to exploit price fluctuations over time, but have a comparably bad efficiency over short periods of time.
In this paper, we consider the decision problem of a power producer who sells electricity from wind turbines on the continuous intraday market and possesses two storage devices: a battery and a hydrogen based storage system. The problem is solved with a backwards approximate dynamic programming algorithm with optimal computing budget allocation. Numerical results show the algorithm’s high solution quality. Furthermore, tests on real-world data demonstrate the value of using both storage types and investigate the effect of the storage parameters on profit.
Keywords: renewable energy, hydrogen storage, hybrid energy storage system, backwards approximate dynamic programming, optimal computing budget allocation
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